An improved predator-prey particle swarm optimization algorithm for Nash equilibrium solution.

ABSTRACT: Focusing on the problem incurred during particle swarm optimization (PSO) that tends to fall into local optimization when solving Nash equilibrium solutions of games, as well as the problem of slow convergence when solving higher order game pay off matrices, this paper proposes an improved Predator-Prey particle swarm optimization (IPP-PSO) algorithm based on a Predator-Prey particle swarm optimization (PP-PSO) algorithm. First, the convergence of the algorithm is advanced by improving the distribution of the initial predator and prey. By improving the inertia weight of both predator and prey, the problem of "precocity" of the algorithm is improved. By improving the formula used to represent particle velocity, the problems of local optimizations and slowed convergence rates are solved. By

SUBMITTER: Meng Y 

PROVIDER: S-EPMC8612571 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature